The invention relates generally to information retrieval, and more particularly to methods and systems for context-based information retrieval.
Diagnostic imaging systems have emerged into an essential aspect of patient care. Medical images that are obtained via the diagnostic imaging sessions have evolved as tools that allow a clinician non-invasive means to view anatomical cross-sections of internal organs, tissues, bones and other anatomical regions of a patient. More particularly, the medical images serve the clinician in diagnosis of disease states, determination of suitable treatment options and/or monitoring the effects of treatment, to name a few. As will be appreciated, medical images may be obtained from a broad spectrum of imaging modalities, such as, but not limited to computed tomography (CT) imaging, ultrasound imaging, magnetic resonance (MR) imaging, digital mammography, X-ray imaging, nuclear medicine imaging, or positron emission tomography (PET) imaging, or combinations of the above.
Additionally, the diagnostic imaging systems may also be configured to generate one or more log files. As will be appreciated, a log file may be representative of a file that lists actions that have occurred. More particularly, the log file may include functions and activities performed by the imaging system, often in a time-associated format, for example. Furthermore, the log file may include data representative of events, errors, machine critical parameters, sensor outputs, or a combination thereof. Accordingly, these log files may be used by a technician to facilitate detection of faults associated with the diagnostic imaging system and subsequent diagnosis and/or servicing.
As will be appreciated, these log files typically include a substantial amount of data. Accordingly, analyzing the log files to retrieve relevant information is a tedious and cumbersome process. A wide array of techniques has been developed to aid in the retrieval of relevant information from the log files. Unfortunately, the large amount of log data that must be analyzed may overwhelm the presently available techniques, thereby resulting in a time-consuming and often error-prone process. This may be especially problematic in systems that handle high volumes of log data. Furthermore, analysis of the large amount of data in the log files may inordinately lead to delays in fault detection, diagnosis and subsequent servicing of the diagnostic imaging system, and may adversely affect system availability.
Additionally, the presently available techniques for information retrieval are typically generic in nature, and fail to provide domain specific information. In other words, the techniques currently in use generally employ probabilistic, statistical and/or adaptive approaches to retrieve information. However, these generic techniques fail to respond to complex information retrieval and domain specific rules.
It may therefore be desirable to develop a robust technique and system for the systematic retrieval of domain specific information that advantageously facilitates substantially superior fault detection, diagnosis and service of the diagnostic imaging system. In particular, there is a need for a system that may be configured to aid in enhancing ease of analyzing log data, thereby simplifying the maintenance workflow of the diagnostic imaging system.